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High-speed Particle Image Velocimetry Near Surfaces
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Accurate velocity estimation from surface-consistent residual statics.

Ahmad Muhammad1, Paul Edigbue2, Sherif Hanafy1

  • 1Department of Geosciences, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.

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|October 7, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new method to accurately estimate Normal Moveout (NMO) velocities using residual time shifts. The technique improves seismic data processing and subsurface imaging by minimizing errors and enhancing signal quality.

Keywords:
Normal moveout (NMO) velocityResidual static correctionSeismic data processingVelocity estimation

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Area of Science:

  • Geophysics
  • Seismic Data Processing

Background:

  • Accurate Normal Moveout (NMO) velocity estimation is crucial for seismic data processing.
  • Imperfect NMO corrections can lead to residual time shifts, impacting subsurface imaging quality.

Purpose of the Study:

  • To develop a novel methodology for accurate NMO velocity estimation.
  • To utilize residual static components from imperfect NMO corrections to refine velocity models.

Main Methods:

  • The proposed algorithm analyzes residual static components to estimate optimal NMO velocities.
  • The method was tested on both synthetic and real seismic datasets.

Main Results:

  • The algorithm demonstrated high accuracy, with velocity estimates showing minimal deviation from true model velocities (0.05% on synthetic data).
  • Application to real 2D seismic data yielded NMO velocities with only a 0.6% difference compared to expert-derived values.

Conclusions:

  • The novel methodology provides a robust and accurate approach to NMO velocity estimation.
  • This technique minimizes human error, improves seismic event flattening, and enhances the signal-to-noise ratio (SNR) for better subsurface imaging.